Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnly, idempotent, openWorld and non-destructive, so the safety profile is covered. The description adds real behavioral context beyond them: results are limited to what upstream APIs returned, each carries a source link and identifier, an empty list is a legitimate signal, and the model must not fabricate entries.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Four tight sentences, front-loaded with purpose, then filters, then return semantics, then the anti-fabrication warning. No sentence is redundant and nothing is buried.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return shapes need no explanation, yet the description still clarifies the source-link/identifier payload and the empty-result meaning. Combined with rich annotations, an agent has everything needed to call this correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With schema coverage at 57%, the description compensates well by naming the filters (year_from, year_to, field, open_access, source), enumerating the source values, and explaining that source=all mixes indexes. Only 'limit' and the semantics of year bounds are left solely to the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Search peer-reviewed and preprint records') plus the input mode (question or keywords), which clearly distinguishes it from siblings like get_paper and find_related_papers, which operate on a known paper. An agent can pick this for open-ended discovery without opening the schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is implied by the filters and the source list, and the closing line ('Do not invent papers to fill a gap') gives a genuine anti-hallucination directive for empty results. However, it never states when to prefer this over find_related_papers or get_paper, so sibling routing is left to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.